IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v279y2020ics0306261920313234.html
   My bibliography  Save this article

Handling heterogeneity in frontier modeling of city-level energy efficiency: The case of China

Author

Listed:
  • Zhang, H.
  • Fan, L.W.
  • Zhou, P.

Abstract

Cities have been playing significant role in promoting energy efficiency and driving sustainable development. Energy consumption in different cities usually exhibit different characteristics. It is therefore important to evaluate and compare city-level energy efficiency performance by considering the impact of heterogeneity. This study employed stochastic frontier analysis to assess the spatial and temporal disparity of energy efficiency in Chinese cities in 2005–2015. The energy efficiency disparity across different cities was found to be significant, with energy efficient cities mainly located in more developed regions. We introduced a Mean-Variance Classification approach to address the effects of city heterogeneities and improve assessment reliability. This classification showed better discriminating power through narrowing the gap within groups and widening the gap across different groups. The empirical results reveal that mature cities with steady and high energy efficiency may influence and guide energy efficiency improvement of surrounding areas. To achieve energy efficiency improvement quickly, more attention should be paid to the promising cities with significant energy efficiency fluctuations.

Suggested Citation

  • Zhang, H. & Fan, L.W. & Zhou, P., 2020. "Handling heterogeneity in frontier modeling of city-level energy efficiency: The case of China," Applied Energy, Elsevier, vol. 279(C).
    • Handle: RePEc:eee:appene:v:279:y:2020:i:c:s0306261920313234
    DOI: 10.1016/j.apenergy.2020.115846
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920313234
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.115846?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    2. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    3. Cliff Huang & Tai-Hsin Huang & Nan-Hung Liu, 2014. "A new approach to estimating the metafrontier production function based on a stochastic frontier framework," Journal of Productivity Analysis, Springer, vol. 42(3), pages 241-254, December.
    4. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    5. Boyd, Gale A. & Lee, Jonathan M., 2019. "Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis," Energy Economics, Elsevier, vol. 81(C), pages 159-174.
    6. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    7. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    8. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    9. Zhu, Qingyuan & Li, Xingchen & Li, Feng & Wu, Jie & Zhou, Dequn, 2020. "Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions," Energy Economics, Elsevier, vol. 89(C).
    10. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    11. Li, Ke & Lin, Boqiang, 2015. "Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China," Energy Economics, Elsevier, vol. 48(C), pages 230-241.
    12. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    13. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    14. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    15. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    16. Li, Ming-Jia & Tao, Wen-Quan, 2017. "Review of methodologies and polices for evaluation of energy efficiency in high energy-consuming industry," Applied Energy, Elsevier, vol. 187(C), pages 203-215.
    17. Qi, Xiaoyan & Guo, Pibin & Guo, Yanshan & Liu, Xiuli & Zhou, Xijun, 2020. "Understanding energy efficiency and its drivers: An empirical analysis of China’s 14 coal intensive industries," Energy, Elsevier, vol. 190(C).
    18. Chung, William & Yeung, Iris M.H., 2017. "Benchmarking by convex non-parametric least squares with application on the energy performance of office buildings," Applied Energy, Elsevier, vol. 203(C), pages 454-462.
    19. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    20. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    21. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    22. Li, Ming-Jia & He, Ya-Ling & Tao, Wen-Quan, 2017. "Modeling a hybrid methodology for evaluating and forecasting regional energy efficiency in China," Applied Energy, Elsevier, vol. 185(P2), pages 1769-1777.
    23. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    24. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    25. Xavier Irz & Colin Thirtle, 2004. "Dual Technological Development in Botswana Agriculture: A Stochastic Input Distance Function Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 55(3), pages 455-478, November.
    26. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    27. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhu, Junpeng & Lin, Boqiang, 2022. "Economic growth pressure and energy efficiency improvement: Empirical evidence from Chinese cities," Applied Energy, Elsevier, vol. 307(C).
    2. Yonghan Jeon & Jongoh Nam, 2023. "Estimating Energy Efficiency and Energy Saving Potential in the Republic of Korea’s Offshore Fisheries," Sustainability, MDPI, vol. 15(20), pages 1-17, October.
    3. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(C).
    4. Hongcheng Shen & Zihao Yang & Yuxin Bao & Xiaonuan Xia & Dan Wang, 2022. "Impact of Urban Mining on Energy Efficiency: Evidence from China," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    5. Li, Mengna & Pan, Xiongfeng & Yuan, Sai, 2022. "Do the national industrial relocation demonstration zones have higher regional energy efficiency?," Applied Energy, Elsevier, vol. 306(PA).
    6. Chong Peng & Jingjing Zhang & Zhenyu Xu, 2022. "Does Price Distortion Affect Energy Efficiency? Evidence from Dynamic Spatial Analytics of China," Energies, MDPI, vol. 15(24), pages 1-15, December.
    7. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    8. Zhou, Sheng & Xu, Zhiwei, 2022. "Energy efficiency assessment of RCEP member states: A three-stage slack based measurement DEA with undesirable outputs," Energy, Elsevier, vol. 253(C).
    9. Lin, Boqiang & Zhou, Yicheng, 2021. "Does fiscal decentralization improve energy and environmental performance? New perspective on vertical fiscal imbalance," Applied Energy, Elsevier, vol. 302(C).
    10. Luping Zhang & Yingying Zhu & Liwei Fan, 2021. "Temporal-Spatial Structure and Influencing Factors of Urban Energy Efficiency in China’s Agglomeration Areas," Sustainability, MDPI, vol. 13(19), pages 1-20, October.
    11. Zhou, P. & Zhang, H. & Zhang, L.P., 2022. "The drivers of energy intensity changes in Chinese cities: A production-theoretical decomposition analysis," Applied Energy, Elsevier, vol. 307(C).
    12. Kai Hu & Dandan Li & Daqian Shi & Wenli Xu, 2023. "Environmental regulation and energy efficiency: evidence from daily penalty policy in China," Journal of Regulatory Economics, Springer, vol. 63(1), pages 1-29, April.
    13. Wang, Na & Fu, Xiaodong & Wang, Shaobin & Yang, Hao & Li, Zhen, 2022. "Convergence characteristics and distribution patterns of residential electricity consumption in China: An urban-rural gap perspective," Energy, Elsevier, vol. 254(PB).
    14. Wu, Bangzheng & Yue, Pengpeng & Zuo, Shengqiang, 2023. "Borrow to be the poor or the rich? It depends: Credit market and wealth accumulation," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 804-821.
    15. Cheng, Zhuo & Kai, Zhe & Zhu, Shouwenjun, 2023. "Does green finance regulation improve renewable energy utilization? Evidence from energy consumption efficiency," Renewable Energy, Elsevier, vol. 208(C), pages 63-75.
    16. Krzysztof Księżopolski & Mirosław Drygas & Kamila Pronińska & Iwona Nurzyńska, 2020. "The Economic Effects of New Patterns of Energy Efficiency and Heat Sources in Rural Single-Family Houses in Poland," Energies, MDPI, vol. 13(23), pages 1-19, December.
    17. Che, Xiao-Jing & Zhou, P. & Wang, M., 2022. "The policy effect on photovoltaic technology innovation with regional heterogeneity in China," Energy Economics, Elsevier, vol. 115(C).
    18. Miao, Zhuang & Chen, Xiaodong & Baležentis, Tomas, 2021. "Improving energy use and mitigating pollutant emissions across “Three Regions and Ten Urban Agglomerations”: A city-level productivity growth decomposition," Applied Energy, Elsevier, vol. 283(C).
    19. Wang, Ailun & Hu, Shuo & Lin, Boqiang, 2021. "Emission abatement cost in China with consideration of technological heterogeneity," Applied Energy, Elsevier, vol. 290(C).
    20. Wei, Wei & Hu, Haiqing & Chang, Chun-Ping, 2022. "Why the same degree of economic policy uncertainty can produce different outcomes in energy efficiency? New evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 467-481.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    2. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    3. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    4. Martini, Gianmaria & Scotti, Davide & Viola, Domenico & Vittadini, Giorgio, 2020. "Persistent and temporary inefficiency in airport cost function: An application to Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 999-1019.
    5. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2017. "Determinants of transient and persistent hospital efficiency: The case of Italy," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 5-22, September.
    6. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.
    7. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    8. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    9. Liu, Xiao-Yan & Pollitt, Michael G. & Xie, Bai-Chen & Liu, Li-Qiu, 2019. "Does environmental heterogeneity affect the productive efficiency of grid utilities in China?," Energy Economics, Elsevier, vol. 83(C), pages 333-344.
    10. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    11. Hailu, Kidanemariam Berhe & Tanaka, Makoto, 2015. "A “true” random effects stochastic frontier analysis for technical efficiency and heterogeneity: Evidence from manufacturing firms in Ethiopia," Economic Modelling, Elsevier, vol. 50(C), pages 179-192.
    12. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.
    13. Albalate, Daniel & Rosell, Jordi, 2019. "On the efficiency of toll motorway companies in Spain," Research in Transportation Economics, Elsevier, vol. 76(C).
    14. Subal C. Kumbhakar & Gudbrand Lien, 2017. "Yardstick Regulation of Electricity Distribution Disentangling Short-run and Long-run Inefficiencies," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    15. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.
    16. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    17. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    18. Bernini, Cristina & Cerqua, Augusto & Pellegrini, Guido, 2017. "Public subsidies, TFP and efficiency: A tale of complex relationships," Research Policy, Elsevier, vol. 46(4), pages 751-767.
    19. Vanesa D’Elia & Gustavo Ferro, 2019. "Empirical Efficiency Measurement in Higher Education: An Overview," CEMA Working Papers: Serie Documentos de Trabajo. 708, Universidad del CEMA.
    20. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:279:y:2020:i:c:s0306261920313234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.